# Software Engineer, Research Tooling
**Company:** [Cursor](https://scaleengineer.com/companies/cursor)
A full-stack software engineering role at Cursor focused on building research tooling infrastructure that enables researchers to iterate quickly on AI/ML experiments and extract insights. The position involves designing and deploying comprehensive solutions spanning experiment orchestration platforms, model evaluation visualization tools, and abstractions for understanding model behavior at scale. This is an opportunity to directly impact the development of frontier AI models by creating high-leverage tools and platforms that multiply researcher productivity.
**Role:** Full Stack Engineer
**Seniority:** Mid
**Locations:** Palo Alto, CA
**Salary:** 180000–280000 USD
[Apply](https://jobs.ashbyhq.com/cursor/fa7a821b-ca2b-43fe-8942-07f215a060c7)
Canonical: https://scaleengineer.com/jobs/cursor/software-engineer-research-tooling
---
## Responsibilities

- Full-Stack Application Development: Design, build, and maintain end-to-end applications and infrastructure that researchers depend on daily, spanning experiment setup, configuration management, feedback collection systems, and comprehensive results analysis pipelines. Ensure systems scale efficiently and maintain reliability across the research workflow lifecycle.
- Product Area Ownership: Take complete ownership of research tool product areas from initial user discovery and requirements gathering through design, implementation, testing, and ongoing iteration. Establish architectural patterns and best practices that serve as standards for how research applications are built across the organization.
- Platform and Infrastructure Design: Architect and develop reusable, composable platforms and abstraction layers that accelerate the development of new research applications. Create standardized patterns for experiment orchestration, data visualization, and model evaluation to reduce redundancy and enable rapid iteration cycles.
- Researcher Collaboration and UX Translation: Work embedded with research teams to deeply understand their domain-specific workflows, identify productivity bottlenecks, and translate complex research requirements into intuitive interfaces and user-friendly abstractions. Transform pain points into elegant solutions that make advanced research tasks approachable for teams.
- Rapid Prototyping and Iteration: Move quickly from concept to functional prototype, validate assumptions with real-world usage data, and iterate based on researcher feedback. Balance technical robustness with development velocity to ensure research teams access solutions when they need them most.

## Requirements

### education

- {"name":"Computer Science or Related Field","description":"Bachelor's degree in Computer Science, Software Engineering, or equivalent technical discipline preferred. Equivalent practical experience and demonstrated software engineering competency can substitute for formal degree requirements."}

### technical

- {"name":"Full-Stack Web Development","description":"Demonstrated expertise building complete production-grade applications spanning frontend, backend, and infrastructure layers. Proficiency in modern full-stack architectures and ability to make informed decisions about the entire stack from user interface through persistence layers."}
- {"name":"Frontend Framework Mastery","description":"Strong production experience with React or similar modern frontend frameworks. Ability to build responsive, performant UIs with particular strength in rendering and visualizing structured data, complex interactions, and real-time updates."}
- {"name":"Backend Development","description":"Solid backend engineering skills using TypeScript, Python, Go, or similar languages. Experience designing and implementing APIs, managing state, handling concurrent operations, and building scalable service architectures that support complex workflows."}
- {"name":"Data-Dense UI Development","description":"Proven experience building sophisticated tools for technical users that handle high-volume, structured data. Examples include transcript viewers, diffing systems, code review interfaces, observability dashboards, operational queues, or similar data-rich applications requiring strong data visualization instincts."}
- {"name":"Product Infrastructure and Tooling","description":"Experience building tools, platforms, or developer infrastructure specifically designed for technical end-users such as engineers, researchers, data scientists, or analysts. Understanding of how to design abstractions that improve usability without sacrificing power."}

### experience

- {"name":"Full-Stack Product Development","description":"Minimum 3-4 years of professional experience shipping full-stack products and systems from concept to production. Track record of owning complete features and product areas, demonstrating ability to navigate the entire development lifecycle independently."}
- {"name":"Technical User Tools","description":"Experience building applications specifically for technical audiences (engineers, researchers, data scientists, analysts). Understanding of what makes developer-focused tools effective and intuitive."}
- {"name":"Ambiguity and Self-Direction","description":"Demonstrated ability to move quickly in ambiguous environments, define scope independently, and drive projects from rough concept to reliable, production-ready products. Strong bias toward action and iteration."}
- {"name":"Cross-Functional Collaboration","description":"Experience working directly with domain experts, researchers, or other non-engineering stakeholders to translate requirements into technical solutions. Ability to establish shared understanding and iterate collaboratively."}

## Skills

### required

- {"name":"React or Modern Frontend Framework","description":"Production-grade experience with React, Vue, or similar modern frontend framework. Ability to build responsive, interactive UIs with strong performance characteristics and data handling."}
- {"name":"TypeScript","description":"Comfortable and productive with TypeScript for building type-safe, maintainable frontend and backend code. Understanding of advanced TypeScript patterns and ability to leverage types for better developer experience."}
- {"name":"Backend Language (Python, Node.js/TypeScript, or Go)","description":"Proficiency in at least one backend language. Python is commonly used in AI/ML contexts, Node.js provides continuity with TypeScript, and Go offers performance benefits for infrastructure-heavy workloads."}
- {"name":"Full-Stack Problem Solving","description":"Ability to design and implement solutions across database schema, API design, backend services, and frontend presentation. Comfort making architectural decisions that span the entire system."}
- {"name":"API Design and Integration","description":"Strong understanding of designing clean, usable APIs (REST, GraphQL, or similar). Experience integrating complex backend systems with sophisticated frontends."}

### preferred

- {"name":"Data Visualization and Structured Data Rendering","description":"Experience building tools that handle large datasets, complex hierarchical structures, or real-time data streams. Expertise in rendering, filtering, and interacting with structured information at scale."}
- {"name":"ML/AI Infrastructure Familiarity","description":"Understanding of machine learning workflows, experiment tracking systems, or AI infrastructure is beneficial. Familiarity with concepts like model evaluation, hyperparameter tuning, or distributed computing helps navigate the domain."}
- {"name":"Observability and Monitoring","description":"Experience building observability dashboards, logging systems, or monitoring tools. Understanding of how to surface system behavior and performance metrics effectively to users."}
- {"name":"Database and Query Optimization","description":"Experience optimizing database queries, choosing appropriate data models, and scaling data storage solutions. Understanding of when to use different persistence layers (relational, document, time-series, etc.)."}
- {"name":"Rapid Prototyping Frameworks","description":"Familiarity with tools and approaches that enable fast iteration (Next.js, Remix, rapid API frameworks). Experience shipping features quickly and iterating based on user feedback."}

## Tech stack

### tools

- {"name":"Git and Version Control","description":"Essential for collaborative development, code review, and maintaining code history across complex systems."}
- {"name":"Container Technologies (Docker)","description":"Useful for packaging research applications, ensuring reproducibility, and simplifying deployment across different environments."}
- {"name":"CI/CD Pipelines","description":"Automated testing and deployment tools ensuring code quality and enabling rapid iteration on research tooling."}
- {"name":"API Testing and Debugging Tools","description":"Tools like Postman, Insomnia, or custom test suites for validating API contracts and debugging integration issues."}

### others

- {"name":"WebSocket Communication","description":"Real-time bidirectional communication between frontend and backend, enabling live updates of experiment progress and results."}
- {"name":"API Design Patterns","description":"RESTful or GraphQL approaches to designing clean, maintainable interfaces between frontend applications and backend services."}
- {"name":"Performance Optimization","description":"Techniques for optimizing rendering performance, API response times, and database query efficiency in data-intensive applications."}
- {"name":"User Experience for Technical Users","description":"Design principles and implementation practices specific to building tools for engineers and researchers rather than general consumers."}

### databases

- {"name":"PostgreSQL","description":"Reliable, feature-rich relational database suitable for structured research data, experiment metadata, and complex queries."}
- {"name":"MongoDB or Document Databases","description":"Flexible schema storage useful for evolving research data models and semi-structured experiment configurations."}
- {"name":"Redis","description":"In-memory data store for caching, real-time updates, and managing temporary research state during active experiments."}
- {"name":"Time-Series Databases (InfluxDB, Prometheus)","description":"Specialized storage for logging metrics and monitoring system behavior over time during long-running experiments."}

### languages

- {"name":"TypeScript","description":"Primary full-stack language choice for its type safety and productivity. Enables consistent development across frontend and backend systems."}
- {"name":"Python","description":"Strong choice for backend services, particularly in AI/ML research contexts where extensive scientific libraries and researcher familiarity provide advantages."}
- {"name":"Go","description":"Increasingly popular for high-performance backend services and infrastructure tooling where efficiency and concurrency are priorities."}
- {"name":"JavaScript","description":"Fundamental for frontend development and increasingly used in modern full-stack architectures via Node.js and TypeScript transpilation."}

### frameworks

- {"name":"React","description":"Primary frontend framework for building interactive, component-based user interfaces with strong ecosystem support for data visualization and real-time updates."}
- {"name":"Next.js","description":"Full-stack framework that streamlines the integration between frontend and backend, enabling rapid development of full-stack research applications."}
- {"name":"Node.js","description":"Runtime enabling JavaScript/TypeScript execution on the backend, providing consistency across full-stack development."}
- {"name":"Flask or FastAPI","description":"Python-based backend frameworks commonly used in research contexts, offering simplicity and integration with scientific Python libraries."}

## Benefits

### benefits

- {"name":"High-Impact Product Work","description":"Direct influence on research productivity and the development of frontier AI models. Your tools and infrastructure directly enable breakthrough discoveries."}
- {"name":"Collaborative Research Environment","description":"Work embedded with leading AI researchers and engineering teams, gaining exposure to cutting-edge AI/ML work and maintaining technical growth alongside accomplished peers."}
- {"name":"Rapid Skill Development","description":"Continuous exposure to new technical challenges, evolving AI/ML workflows, and opportunities to ship features at a pace that accelerates professional growth."}
- {"name":"Technical Autonomy","description":"Ownership of complete product areas with freedom to make architectural decisions, choose technologies, and drive projects from conception to production."}
- {"name":"Learning and Development","description":"Access to comprehensive training, conference budgets, and learning opportunities to stay current with evolving full-stack development practices and AI infrastructure trends."}

## Compensation

- **max:** 280000
- **min:** 180000
- **currency:** USD
- **stockOptions:** true

## Interview process

### steps

- {"name":"Initial Technical Screenings","description":"Two to three focused technical conversations assessing full-stack development capabilities, problem-solving approach, and system design thinking. Expect discussion of past projects, technical decision-making, and architecture patterns you've used."}
- {"name":"Take-Home or Live Coding Exercise","description":"A practical coding exercise demonstrating full-stack capabilities. May involve building a small feature or solving a design challenge that spans frontend and backend concerns. Typically reflects real research tooling problems."}
- {"name":"Onsite Collaborative Project","description":"In-person session at Cursor's San Francisco office where you'll work on a small project with team members, discuss technical ideas and architectural approaches, and collaborate with engineers building research tools."}
- {"name":"Team and Culture Fit Discussion","description":"Conversations with current team members about collaboration style, approach to ambiguity, and how you think about shipping products for technical users. Emphasis on assessing cultural alignment and teamwork philosophy."}

## Full description
SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars.  
  
SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next.

## About the role

As a Software Engineer on the Research Tools team, you'll build the infrastructure and applications that enable our researchers to iterate quickly, run complex experiments, and extract insights. This is a full-stack product-engineering role.

You'll work directly with researchers and engineers to deeply understand their workflows, identify bottlenecks, and rapidly ship solutions that multiply their productivity. Whether you're creating platforms for experiment orchestration, developing novel visualization tools for model evaluation, or building abstractions for understanding model behavior at scale, your work will directly accelerate our mission of building frontier AI models.

We're looking for someone who can jump into new problems, quickly develop domain expertise, and independently drive impactful projects from conception to delivery. No prior ML or research experience is required.

## What you’ll do

* Build and maintain the full-stack applications and infrastructure researchers rely on daily, covering experiment setup, feedback collection, and results analysis.
* Own complete product areas from user needs through design, implementation, and iteration, setting standards for how to build research applications.
* Create reusable platforms and tools that speed up new research applications, then prototype, ship, and iterate quickly based on real-world usage.
* Partner with research teams to turn their workflows and pain points into intuitive interfaces and abstractions that make complex research tasks fast and approachable.

## You may be a fit if

* You’ve had experience building tools, platforms, or infrastructure for technical users (engineers, researchers, data scientists, analysts, etc.)
* You’ve shipped full-stack products and owned systems from user interface to storage or services, using technologies such as TypeScript and React alongside Node, Python, or Go.
* You’ve built dense, data-facing tools such as transcript viewers, diffing systems, review queues, observability products, or operational dashboards—and you have strong opinions about how structured data should be rendered.
* You have strong product instincts, can identify the right problems to solve, and can move from concept to working prototype with ease.
* You move quickly under ambiguity, collaborate closely with researchers and domain experts, and take open-ended problems from rough need to reliable product.

## Applying

If there appears to be a fit, we'll reach out to schedule 2-3 short technicals. After, we'll schedule an onsite in our office, where you'll work on a small project, discuss ideas, and meet the team.